Expected Efficiency Ranks from Parametric Stochastic Frontier Models

Posted: 15 Mar 2015

See all articles by Seth Richards-Shubik

Seth Richards-Shubik

Lehigh University - Department of Economics; National Bureau of Economic Research (NBER)

William C. Horrace

Syracuse University - Department of Economics

Ian A Wright

Western Sydney University

Date Written: March 13, 2015

Abstract

In the stochastic frontier model, we extend the multivariate probability statements of Horrace (J Econom, 126:335-354, 2005) to calculate the conditional probability that a firm is any particular efficiency rank in the sample. From this, we construct the conditional expected efficiency rank for each firm. Compared to the traditional ranked efficiency point estimates, firm-level conditional expected ranks are more informative about the degree of uncertainty of the ranking. The conditional expected ranks may be useful for empiricists. A Monte Carlo study and an empirical example are provided.

Keywords: Efficiency estimation, Order statistics, Multivariate inference, Multiplicity

JEL Classification: C12, C16, C44, D24

Suggested Citation

Richards-Shubik, Seth and Horrace, William C. and Wright, Ian A, Expected Efficiency Ranks from Parametric Stochastic Frontier Models (March 13, 2015). Empirical Economics, Vol. 48, No. 2, 2015, Available at SSRN: https://ssrn.com/abstract=2577964

Seth Richards-Shubik (Contact Author)

Lehigh University - Department of Economics ( email )

620 Taylor Street
Bethlehem, PA 18015
United States

HOME PAGE: http://www.lehigh.edu/~ser315

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

William C. Horrace

Syracuse University - Department of Economics ( email )

Syracuse, NY 13244-1020
United States
315-443-9061 (Phone)
315-443-1081 (Fax)

HOME PAGE: http://faculty.maxwell.syr.edu/whorrace

Ian A Wright

Western Sydney University ( email )

PO Box 10
Kingswood, NSW 2747
Australia

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